agent-collab 0.1.0

A general-purpose coordination protocol and CLI for multiple AI coding agents working on one repository.

Agent Collab

A general-purpose coordination protocol and artifact generator for multiple AI coding agents working on one repository.

Overview

Agent Collab is a repository orchestration protocol for AI coding agents, automation workflows, and human coordinators. It gives a team of agents a shared operating model for working on the same codebase without overwriting each other, losing context, duplicating work, or merging unreviewed changes.

The core idea is simple:

• Each agent works in its own git worktree.
• Each agent owns a clearly scoped role, branch, and task.
• The repository is the durable source of truth.
• Agents communicate through structured files, diffs, commits, reviews, test reports, and handoff notes.
• Protected branches are not edited directly.
• Human approval remains required for destructive, ambiguous, production-affecting, or security-sensitive decisions.

This repository is both:

• A portable agent instruction package, with SKILL.md as the agent-facing entry point for runtimes that support skill-style instructions.
• A pip-installable CLI package, with the agent-collab command for creating standardized .agent/ coordination files.

Why This Exists

AI agents are effective at focused coding tasks, but multi-agent work fails quickly when agents share one working directory or rely on hidden chat state. Common failure modes include:

• Two agents editing the same files without knowing it.
• A reviewer seeing final files but not the diff.
• A tester not knowing which branch or worktree was tested.
• An implementer claiming checks passed without actually running them.
• Architectural decisions living only in a conversation transcript.
• Generated files, lockfiles, migrations, or secrets slipping into a branch unnoticed.
• Integration happening without a clear handoff, review, test report, or rollback plan.

Agent Collab addresses these failures by making coordination explicit, durable, and reviewable.

What Agent Collab Provides

• Worktree-first collaboration rules
• Branch naming conventions for agent-owned work
• Role playbooks for coordinator, architect, implementer, reviewer, tester, documentation, and integration agents
• Structured .agent/ repository state
• Task, handoff, review, test report, ADR, risk, conflict, ownership, and merge recommendation templates
• Security and escalation rules for high-risk changes
• A Typer-based CLI for creating coordination artifacts consistently
• A quality gate for merge readiness

Repository Layout

agent-collab/
  pyproject.toml
  SKILL.md
  README.md
  agents/
    openai.yaml
  references/
    artifacts-and-templates.md
    quality-review-testing-merge.md
    role-playbooks.md
    security-and-escalation.md
    worktree-and-branch-protocol.md
  src/
    agent_collab/
      cli.py
      coordination.py
  tests/
    test_cli.py
    test_coordination.py

SKILL.md

The agent-facing runtime instructions. Any compatible agent runtime can load this file, and humans can also use it as the concise operating guide.

agents/openai.yaml

Optional runtime metadata for platforms that read skill catalog metadata. It is not required for standalone use.

references/

Detailed playbooks that keep SKILL.md concise while preserving a comprehensive protocol.

src/agent_collab/

The installable Python package. cli.py contains the Typer CLI and coordination.py contains the artifact-generation logic.

Installation And Use

Install the CLI directly from GitHub:

python3 -m pip install "git+https://github.com/egesabanci/agent-collab.git"

Or clone this repository wherever you keep shared agent instructions or workflow tools:

git clone [e-mail]:egesabanci/agent-collab.git
cd agent-collab

Then install the CLI from the local checkout:

python3 -m pip install .

For local development, install it in editable mode:

python3 -m pip install -e .

Use it in any of these ways:

• Ask an agent to follow SKILL.md.
• Place this folder in your agent runtime's skill, plugin, or instruction directory if it supports one.
• Run the agent-collab CLI to create .agent/ coordination artifacts.
• Have human coordinators use the README and reference files as the team protocol.

Example agent prompt:

Use Agent Collab to coordinate multiple coding agents safely on this repository task.

Quick Start

From the repository where agents will collaborate, initialize the coordination directory:

agent-collab init

Create a task:

agent-collab new-task \
  --id TASK-001 \
  --title "API Client Refactor" \
  --owner coordinator \
  --risk medium \
  --check lint \
  --check typecheck \
  --check tests \
  --check build

Create role worktrees:

git fetch origin
git worktree add ../repo-implementer -b agent/impl/TASK-001-api-client-refactor origin/main
git worktree add ../repo-reviewer -b agent/review/TASK-001-api-client-refactor origin/main
git worktree add ../repo-tester -b agent/test/TASK-001-api-client-refactor origin/main

After implementation, create a handoff:

agent-collab handoff \
  --task TASK-001-api-client-refactor \
  --role implementer \
  --branch agent/impl/TASK-001-api-client-refactor \
  --worktree ../repo-implementer

Create review and test reports:

agent-collab review \
  --task TASK-001-api-client-refactor \
  --branch agent/impl/TASK-001-api-client-refactor

agent-collab test-report \
  --task TASK-001-api-client-refactor \
  --branch agent/impl/TASK-001-api-client-refactor

Prepare merge readiness:

agent-collab merge-recommendation \
  --task TASK-001-api-client-refactor \
  --recommendation needs_changes \
  --risk medium \
  --human-approval-required yes

The .agent/ Directory

Agent Collab creates and uses a .agent/ directory in the target repository:

.agent/
  README.md
  status.json
  tasks/
  handoffs/
  decisions/
  reviews/
  test-reports/
  risks/
  protocols/
  scratch/

This directory is the durable memory layer for the agent team.

.agent/status.json

Tracks the active task, current phase, protected branches, assigned agents, and merge readiness.

Only a coordinator agent or explicitly assigned agent should update this file. If ownership is unclear, write a handoff or risk note instead of racing on shared state.

.agent/tasks/

Contains scoped task definitions with:

• Goal
• Non-goals
• Context
• Scope
• Acceptance criteria
• Required checks
• Risk level
• Dependencies
• Open questions
• Final result

.agent/handoffs/

Contains structured handoffs between roles.

A valid handoff answers:

• What changed?
• Why did it change?
• Where did it change?
• How was it verified?
• What risks remain?
• What should the next agent do?

.agent/decisions/

Contains ADRs for architectural decisions.

Use ADRs for changes to:

• System boundaries
• Authentication or authorization behavior
• Data models
• API contracts
• Runtime architecture
• Deployment topology
• External services
• Error handling policy
• Queue or job architecture
• Security-sensitive patterns

.agent/reviews/

Contains reviewer output. Reviewers must inspect the diff, not just final files.

Reviews cover:

• Task alignment
• Correctness
• Architecture
• Security
• Reliability
• Maintainability
• Test coverage
• Scope control
• Rollback safety

.agent/test-reports/

Contains verification evidence:

• Environment
• Commands run
• Result table
• Failures
• Suspected cause
• Reproduction steps
• Coverage gaps
• Recommendation

.agent/risks/

Contains conflicts, blockers, high-risk notes, and human decision requests.

Use this directory when two agents touch overlapping files or when a decision needs human approval.

.agent/protocols/

Contains task-specific protocols, especially file ownership maps for parallel work.

Agent Roles

Agent Collab defines a small set of roles. Use only the roles needed for the task.

Role	Purpose
Coordinator	Scope, sequencing, assignment, worktree routing, merge recommendation
Architect	Design, boundaries, ADRs, risk analysis, test strategy
Implementer	Scoped code changes, tests, commits, implementation handoff
Reviewer	Diff review for correctness, architecture, security, reliability, maintainability
Tester	Verification, reproduction, smoke tests, test reports
Documentation	README, docs, examples, migration notes, operational notes
Integration	Conflict resolution, branch freshness, final checks, merge readiness

Standard Agent Workflow

Every agent should begin by confirming:

1. Role
2. Assigned task
3. Branch
4. Worktree
5. Task file
6. Relevant handoffs
7. Relevant ADRs
8. Current git status
9. Project check commands
10. Planned next action

Before editing, an agent should run:

git status
git branch --show-current
git log --oneline -5

Before handoff, an agent should run:

git status
git diff
git diff --stat

CLI Reference

The CLI is built with Typer and installed as agent-collab.

Run from the target repository root:

agent-collab <command>

Or pass an explicit target:

agent-collab <command> --root /path/to/repo

The command examples below assume the package is installed in your current Python environment.

init

Create the .agent/ directory structure.

agent-collab init \
  --project example-project \
  --phase planning \
  --protected-branches main,master,production,staging

new-task

Create a task file.

agent-collab new-task \
  --id TASK-002 \
  --title "Improve checkout error handling" \
  --owner implementer \
  --risk high \
  --check lint \
  --check tests \
  --check build

handoff

Create a role handoff.

agent-collab handoff \
  --task TASK-002-improve-checkout-error-handling \
  --role implementer \
  --branch agent/impl/TASK-002-improve-checkout-error-handling \
  --worktree ../repo-implementer \
  --status needs_review \
  --next-agent reviewer

adr

Create an architecture decision record.

agent-collab adr \
  --number 1 \
  --title "Use Server-Side API Wrapper"

review

Create a review template.

agent-collab review \
  --task TASK-002-improve-checkout-error-handling \
  --branch agent/impl/TASK-002-improve-checkout-error-handling \
  --status changes_requested \
  --recommendation request_changes

test-report

Create a test report template.

agent-collab test-report \
  --task TASK-002-improve-checkout-error-handling \
  --branch agent/impl/TASK-002-improve-checkout-error-handling \
  --recommendation needs_fix

conflict

Create a conflict note.

agent-collab conflict \
  --task TASK-002-improve-checkout-error-handling \
  --title "Checkout API and Billing Boundary" \
  --type architectural \
  --requires-human yes

file-ownership

Create a file ownership map.

agent-collab file-ownership \
  --task TASK-002-improve-checkout-error-handling

human-decision

Create a human decision note.

agent-collab human-decision \
  --task TASK-002-improve-checkout-error-handling \
  --title "Choose Billing Retry Policy" \
  --risk high

merge-recommendation

Create a final merge recommendation.

agent-collab merge-recommendation \
  --task TASK-002-improve-checkout-error-handling \
  --recommendation needs_human_decision \
  --risk high \
  --human-approval-required yes

Worktree Strategy

Agent Collab expects one worktree per agent role or independently owned task slice.

Example:

repo/
../repo-architect/
../repo-implementer-api/
../repo-implementer-ui/
../repo-reviewer/
../repo-tester/
../repo-integration/

Recommended branch names:

agent/architect/TASK-002-api-client-refactor
agent/impl/TASK-002-api-client-refactor
agent/impl-frontend/TASK-002-api-client-refactor
agent/impl-backend/TASK-002-api-client-refactor
agent/review/TASK-002-api-client-refactor
agent/test/TASK-002-api-client-refactor
agent/docs/TASK-002-api-client-refactor
agent/integration/TASK-002-api-client-refactor

Safe Parallelization

Parallel work is safest when agents own different parts of the system.

Good split:

Agent A: backend API route
Agent B: frontend UI state
Agent C: documentation
Agent D: tests

Risky split:

Agent A: auth middleware
Agent B: API client
Agent C: session handling
Agent D: routing layer

Risky splits require a file ownership map and explicit integration plan.

Merge Readiness

A task is merge-ready only when:

• Acceptance criteria are met.
• Scope is controlled.
• Implementation handoff exists.
• Review exists.
• Required checks were run or skipped with clear justification.
• Test report exists for non-trivial changes.
• No blocking questions remain.
• No unresolved high-risk issues remain.
• No secrets are present.
• Rollback path is documented.
• Human approval exists where required.

Security Model

Agent Collab treats these areas as high risk:

• Authentication
• Authorization
• User identity
• Sessions and cookies
• CSRF and CORS
• Billing and payments
• Webhooks
• Admin panels
• Database migrations
• File uploads
• Multi-tenant data access
• PII handling
• Logging or analytics containing user data
• Deployment secrets
• Infrastructure configuration

High-risk changes require focused review and often human approval.

If a secret is committed, stop and escalate. Do not merely delete it in a later commit and continue.

What Agent Collab Is Not

Agent Collab is not:

• A replacement for CI.
• A replacement for GitHub branch protection.
• A replacement for human architectural judgment.
• A merge bot.
• A distributed locking system.
• A guarantee that parallel work will never conflict.

It is a protocol and artifact generator that makes multi-agent work more explicit, inspectable, and recoverable.

Validation

If your agent runtime provides a package or skill validator, run it against the repository root. At minimum, validate the frontmatter and metadata YAML:

python3 - <<'PY'
from pathlib import Path
import yaml

skill = Path("SKILL.md").read_text()
yaml.safe_load(skill.split("---", 2)[1])
yaml.safe_load(Path("agents/openai.yaml").read_text())
print("metadata ok")
PY

Validate the package and CLI with:

python3 -B -m py_compile src/agent_collab/*.py
agent-collab --help

Run the unit test suite:

python3 -m pip install -e ".[dev]"
python3 -m pytest

Smoke-test artifact generation in a temporary directory:

tmpdir="$(mktemp -d)"
agent-collab init --root "$tmpdir" --project demo
agent-collab new-task --root "$tmpdir" --id TASK-001 --title "Demo Task"
find "$tmpdir/.agent" -maxdepth 2 -type f | sort
rm -rf "$tmpdir"

Development Notes

Keep SKILL.md concise and agent-facing. Put detailed protocol material in references/, and keep deterministic, repeatable generation behavior in src/agent_collab/.

When changing the protocol:

1. Update SKILL.md only if the runtime entry point changes.
2. Update the relevant reference file for detailed behavior.
3. Update src/agent_collab/coordination.py when templates or artifact names change, and src/agent_collab/cli.py when command behavior changes.
4. Run validation and a temp-dir smoke test.
5. Use a conventional commit message.

Suggested Repository Description

A general-purpose coordination protocol for multiple AI coding agents working on one repository with worktree isolation, structured handoffs, review, testing, and merge readiness.

License

Agent Collab is released under the MIT License. See LICENSE.